{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%config IPCompleter.greedy=True\n",
    "from tensorflow import keras\n",
    "import matplotlib as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv('./Advertising.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x = data[data.columns[1:-1]]\n",
    "y = data.iloc[:,-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model = keras.Sequential()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model.add(keras.layers.Dense(1,input_dim=3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model.compile(optimizer='adam',loss='mse')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/2000\n",
      "200/200 [==============================] - 0s 946us/step - loss: 21007.0648\n",
      "Epoch 2/2000\n",
      "200/200 [==============================] - 0s 95us/step - loss: 20609.7300\n",
      "Epoch 3/2000\n",
      "200/200 [==============================] - 0s 100us/step - loss: 20196.4558\n",
      "Epoch 4/2000\n",
      "200/200 [==============================] - 0s 90us/step - loss: 19800.0877\n",
      "Epoch 5/2000\n",
      "200/200 [==============================] - 0s 100us/step - loss: 19410.3833\n",
      "Epoch 6/2000\n",
      "200/200 [==============================] - 0s 90us/step - loss: 18998.0613\n",
      "Epoch 7/2000\n",
      "200/200 [==============================] - 0s 88us/step - loss: 18601.5447\n",
      "Epoch 8/2000\n",
      "200/200 [==============================] - 0s 96us/step - loss: 18218.1396\n",
      "Epoch 9/2000\n",
      "200/200 [==============================] - 0s 92us/step - loss: 17828.1509\n",
      "Epoch 10/2000\n",
      "200/200 [==============================] - 0s 90us/step - loss: 17463.7438\n",
      "Epoch 11/2000\n",
      "200/200 [==============================] - 0s 95us/step - loss: 17097.8945\n",
      "Epoch 12/2000\n",
      "200/200 [==============================] - 0s 86us/step - loss: 16746.0022\n",
      "Epoch 13/2000\n",
      "200/200 [==============================] - 0s 90us/step - loss: 16390.7739\n",
      "Epoch 14/2000\n",
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      "Epoch 15/2000\n",
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      "Epoch 16/2000\n",
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      "Epoch 17/2000\n",
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      "Epoch 18/2000\n",
      "200/200 [==============================] - 0s 79us/step - loss: 14722.6270\n",
      "Epoch 19/2000\n",
      "200/200 [==============================] - 0s 93us/step - loss: 14418.9597\n",
      "Epoch 20/2000\n",
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      "Epoch 21/2000\n",
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      "Epoch 22/2000\n",
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      "Epoch 23/2000\n",
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      "Epoch 31/2000\n",
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      "Epoch 32/2000\n",
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      "Epoch 33/2000\n",
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      "Epoch 34/2000\n",
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      "Epoch 36/2000\n",
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      "Epoch 40/2000\n",
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      "Epoch 46/2000\n",
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      "Epoch 47/2000\n",
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      "Epoch 48/2000\n",
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      "Epoch 49/2000\n",
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      "Epoch 50/2000\n",
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      "Epoch 53/2000\n",
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      "Epoch 54/2000\n",
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      "Epoch 55/2000\n",
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      "Epoch 56/2000\n",
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      "Epoch 57/2000\n",
      "200/200 [==============================] - 0s 91us/step - loss: 6332.6965\n",
      "Epoch 58/2000\n",
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      "Epoch 59/2000\n",
      "200/200 [==============================] - 0s 92us/step - loss: 6068.7988\n",
      "Epoch 60/2000\n",
      "200/200 [==============================] - 0s 90us/step - loss: 5934.8580\n",
      "Epoch 61/2000\n",
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      "Epoch 62/2000\n",
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      "Epoch 63/2000\n",
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      "Epoch 64/2000\n",
      "200/200 [==============================] - 0s 96us/step - loss: 5462.6500\n",
      "Epoch 65/2000\n",
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      "Epoch 66/2000\n",
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      "Epoch 67/2000\n",
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      "Epoch 68/2000\n",
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      "Epoch 69/2000\n",
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      "Epoch 70/2000\n",
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      "Epoch 71/2000\n",
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      "Epoch 72/2000\n",
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      "Epoch 73/2000\n",
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      "Epoch 74/2000\n",
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      "Epoch 75/2000\n",
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      "Epoch 76/2000\n",
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      "Epoch 77/2000\n",
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      "Epoch 78/2000\n",
      "200/200 [==============================] - 0s 86us/step - loss: 4160.6129\n",
      "Epoch 79/2000\n",
      "200/200 [==============================] - 0s 80us/step - loss: 4085.7954\n",
      "Epoch 80/2000\n",
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      "Epoch 81/2000\n",
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      "Epoch 82/2000\n",
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      "Epoch 83/2000\n",
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      "Epoch 84/2000\n",
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      "Epoch 85/2000\n",
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      "Epoch 86/2000\n",
      "200/200 [==============================] - 0s 86us/step - loss: 3607.4679\n",
      "Epoch 87/2000\n",
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      "Epoch 88/2000\n",
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      "Epoch 89/2000\n",
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      "Epoch 90/2000\n",
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      "Epoch 91/2000\n",
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      "Epoch 92/2000\n",
      "200/200 [==============================] - 0s 82us/step - loss: 3278.0156\n",
      "Epoch 93/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "200/200 [==============================] - 0s 85us/step - loss: 3226.4762\n",
      "Epoch 94/2000\n",
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      "Epoch 95/2000\n",
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      "Epoch 96/2000\n",
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      "Epoch 97/2000\n",
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      "Epoch 98/2000\n",
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      "Epoch 99/2000\n",
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      "Epoch 100/2000\n",
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      "Epoch 102/2000\n",
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      "Epoch 103/2000\n",
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      "Epoch 104/2000\n",
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      "Epoch 105/2000\n",
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      "Epoch 106/2000\n",
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      "Epoch 110/2000\n",
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      "Epoch 111/2000\n",
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      "Epoch 112/2000\n",
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      "Epoch 117/2000\n",
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      "Epoch 118/2000\n",
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      "Epoch 131/2000\n",
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      "Epoch 132/2000\n",
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      "Epoch 138/2000\n",
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      "Epoch 139/2000\n",
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      "Epoch 143/2000\n",
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      "Epoch 144/2000\n",
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      "Epoch 159/2000\n",
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      "Epoch 163/2000\n",
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      "Epoch 164/2000\n",
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      "Epoch 165/2000\n",
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      "Epoch 169/2000\n",
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      "Epoch 170/2000\n",
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      "Epoch 171/2000\n",
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      "Epoch 172/2000\n",
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      "Epoch 173/2000\n",
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      "Epoch 174/2000\n",
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      "Epoch 175/2000\n",
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      "Epoch 177/2000\n",
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      "Epoch 178/2000\n",
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      "Epoch 180/2000\n",
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      "Epoch 181/2000\n",
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      "Epoch 182/2000\n",
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      "Epoch 183/2000\n",
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      "Epoch 184/2000\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "200/200 [==============================] - 0s 87us/step - loss: 129.2141\n",
      "Epoch 390/2000\n",
      "200/200 [==============================] - 0s 90us/step - loss: 127.2431\n",
      "Epoch 391/2000\n",
      "200/200 [==============================] - 0s 90us/step - loss: 125.3645\n",
      "Epoch 392/2000\n",
      "200/200 [==============================] - 0s 94us/step - loss: 123.5185\n",
      "Epoch 393/2000\n",
      "200/200 [==============================] - 0s 91us/step - loss: 121.7612\n",
      "Epoch 394/2000\n",
      "200/200 [==============================] - 0s 100us/step - loss: 119.9219\n",
      "Epoch 395/2000\n",
      "200/200 [==============================] - 0s 88us/step - loss: 118.2059\n",
      "Epoch 396/2000\n",
      "200/200 [==============================] - 0s 90us/step - loss: 116.4519\n",
      "Epoch 397/2000\n",
      "200/200 [==============================] - 0s 92us/step - loss: 114.6575\n",
      "Epoch 398/2000\n",
      "200/200 [==============================] - 0s 95us/step - loss: 112.8886\n",
      "Epoch 399/2000\n",
      "200/200 [==============================] - 0s 84us/step - loss: 111.2504\n",
      "Epoch 400/2000\n",
      "200/200 [==============================] - 0s 87us/step - loss: 109.4383\n",
      "Epoch 401/2000\n",
      "200/200 [==============================] - 0s 90us/step - loss: 107.8903\n",
      "Epoch 402/2000\n",
      "200/200 [==============================] - 0s 79us/step - loss: 106.1973\n",
      "Epoch 403/2000\n",
      "200/200 [==============================] - 0s 76us/step - loss: 104.4865\n",
      "Epoch 404/2000\n",
      "200/200 [==============================] - 0s 90us/step - loss: 102.9201\n",
      "Epoch 405/2000\n",
      "200/200 [==============================] - 0s 79us/step - loss: 101.2887\n",
      "Epoch 406/2000\n",
      "200/200 [==============================] - 0s 77us/step - loss: 99.7634\n",
      "Epoch 407/2000\n",
      "200/200 [==============================] - 0s 82us/step - loss: 98.1002\n",
      "Epoch 408/2000\n",
      " 32/200 [===>..........................] - ETA: 0s - loss: 115.4738"
     ]
    }
   ],
   "source": [
    "model.fit(x,y,epochs=2000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model.predict(pd.DataFrame([[300,0,0]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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